code: def forward(self, input, target):
      neg_abs = -input.abs()
      loss = (
          input.clamp(min=0)
          - input * target
          + (1 + neg_abs.exp()).log()
      )
      return loss.mean()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import torch
  import torch.nn.functional
  from torch import nn
  from torch.autograd import Variable
label_desc: Use image node_id 2 for calling the StableBCELoss obj's underlying member method code with example usage: obj.forward(input, target) and returns: loss